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DTSTAMP:20240214T070245Z
LOCATION:Meeting Room C4.9+C4.10\, Level 4 (Convention Centre)
DTSTART;TZID=Australia/Melbourne:20231213T153000
DTEND;TZID=Australia/Melbourne:20231213T154500
UID:siggraphasia_SIGGRAPH Asia 2023_sess168_papers_711@linklings.com
SUMMARY:Projective Sampling for Differentiable Rendering of Geometry
DESCRIPTION:Technical Papers\n\nZiyi Zhang, Nicolas Roussel, and Wenzel Ja
 kob (Ecole Polytechnique Fédérale de Lausanne)\n\nDiscontinuous visibility
  changes at object boundaries remain a persistent source of difficulty in 
 the area of differentiable rendering. Left untreated, they bias computed g
 radients so severely that even basic optimization tasks fail.\n\nPrior pat
 h-space methods addressed this bias by decoupling boundaries from the inte
 rior, allowing each part to be handled using specialized Monte Carlo sampl
 ing strategies. While conceptually powerful, the full potential of this id
 ea remains unrealized since existing methods often fail to adequately samp
 le the boundary proportional to its contribution.\n\nThis paper presents t
 heoretical and algorithmic contributions. On the theoretical side, we tran
 sform the boundary derivative into a remarkably simple local integral that
  invites present and future developments.\n\nBuilding on this result, we p
 ropose a new strategy that projects ordinary samples produced during forwa
 rd rendering onto nearby boundaries. The resulting projections establish a
  variance-reducing guiding distribution that accelerates convergence of th
 e subsequent differential phase.\n\nWe demonstrate the superior efficiency
  and versatility of our method across a variety of shape representations, 
 including triangle meshes, implicitly defined surfaces, and cylindrical fi
 bers based on Bézier curves.\n\nRegistration Category: Full Access\n\nSess
 ion Chair: Soo-Mi Choi (Sejong University)
URL:https://asia.siggraph.org/2023/full-program?id=papers_711&sess=sess168
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